Reducing Readmission After Complex Cancer Surgery

Overview: Following an initial hospitalization for complex cancer surgery, the rate of return to the hospital (readmission) is very high, occurring in one of every five patients. In addition, the cost of all unplanned readmissions in Medicare patients is exorbitant, at over $17 billion. This research evaluates the causes of poor outcomes, such as readmission, in a health care system using the Systems Engineering Initiative for Patient Safety (SEIPS) model. The SEIPS model provides a detailed look at the complex interplay of factors (i.e., patient/caregiver, technology and tools, tasks, organization, and environment) that influences the risk of readmission, rather than placing blame on any one particular person or part of the system. Although large dataset analyses have delineated some of the clinical risk factors for readmission, there is a paucity of data evaluating the risk factors from the patient’s perspective. In addition, no study has evaluated the etiology for readmission using a human factors and systems engineering approach. Because of this gap, it is likely that there are missed opportunities to improve the quality of care for cancer patients by decreasing the readmission rate after surgery. This is particularly important since these operations are planned, resulting in a window of opportunity before surgery where an intervention could occur to decrease the risk of readmission.

Aims: The goals of the project include assessing the cause of readmission from the patient and caregiver’s perspective and assessing the clinical risk factors associated with increased risk of readmission.

Method: This project seeks to apply a systems engineering approach to evaluate the cause of readmission in patients who have undergone complex cancer surgery and were readmitted within 30 days, evaluating the perspective of the patient and his/her caregivers as the central figures in the analysis.  These patient derived risk factors will be incorporated into a known readmission reduction tool, the C-TraC protocol, developed at University of Wisconsin. After obtaining the data included in this proposal, this surgery-specific, patient-centered readmission reduction tool will be tested in a follow-up study to evaluate whether it will decrease the readmission rates for these complex patients.

Funding: ICTR Pilot Projects program

Sharon M. Weber, MD
Section of Surgical Oncology, Division of General Surgery
Vice Chair, Division of General Surgery, Academic Affairs
School of Medicine and Public Health
University of Wisconsin-Madison

Pascale Carayon, PhD
Procter & Gamble Bascom Professor in Total Quality
Department of Industrial and Systems Engineering
Director, Center for Quality and Productivity Improvement
University of Wisconsin-Madison

Caprice C. Greenberg, MD, MPH
Associate Professor, Surgery
School of Medicine and Public Health
Director, Wisconsin Surgical Outcomes Research Program
University of Wisconsin-Madison

Amy Kind, MD, PhD
Assistant Professor, Geriatrics
School of Medicine and Public Health
Director, Madison VA Coordinated Translational Care
University of Wisconsin-Madison

Tamara LeCaire, PhD
Wisconsin Surgical Outcomes Research Program
Department of Surgery, Divisions of Otolaryngology and General Surgery
School of Medicine and Public Health
University of Wisconsin, Madison

Emily R. Winslow, MD, FACS
Assistant Professor
Section of Surgical Oncology, Division of General Surgery
University of Wisconsin-Madison


Acher, A. W., LeCaire, T. J., Hundt, A. S., Greenberg, C. C., Carayon, P., Kind, A. J., & Weber, S. M. (2015). Using human factors and systems engineering to evaluate readmission after complex surgery. J Am Coll Surg, 221(4), 810-820. PMCID: PMC4782927